Abstract
This paper provides a new architecture of neural network, called loop architecture neural network(LANN), and its learning rules. One of its features distinguished from other network, such as Hopfield and bidirectional associative memories, is that it can perform the associative memory among multiple categories. Analysis and simulated results have proved that it is an effective network with excellent convergence.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
References
N. H. Farhat et al.,Applied Optics,24(1985)10, 1469–1475.
J. J. Hopfield, Neurons with graded response have collective computational properties like those of two states neurons. Proceedings of the National Academy of Sciences, USA: 31, May, 1984, 3088–3092.
J. A. Anderson,IEEE Trans. on Systems, Man, and Cybernetics,SMC-13(1983)5, 799–815.
B. Kosko,Applied Optics,26(1981)23, 4974–4959.
Author information
Authors and Affiliations
About this article
Cite this article
Yongjun, Z., Zongzhi, C. Lann and its heteroassociative memory properties. J. of Electron.(China) 13, 11–16 (1996). https://doi.org/10.1007/BF02684709
Issue Date:
DOI: https://doi.org/10.1007/BF02684709